Extended Process to Product Modeling (xPPM) for integrated and seamless IDM and MVD development

Ghang Lee, Young Hyun Park, Sungil Ham

Research output: Contribution to journalArticlepeer-review

40 Citations (Scopus)


This paper proposes a new extended Process to Product Modeling (xPPM) method for integrated and seamless information delivery manual (IDM) and model view definition (MVD) development. Current IDM development typically uses Business Process Modeling Notation (BPMN) to represent a process map (PM). Exchange requirements (ERs) and functional parts (FPs) specify the information required when information is exchanged between different activities. A set of information requirements, specifically defined as a subset of Industry Foundation Classes (IFC), is called an MVD. Currently however, PMs, ERs, FPs, and MVDs are developed as separate documents through independent development steps. Moreover, even though ERs and FPs are designed to be reused, tracking and reusing the ERs and FPs developed by others is practically impossible. The xPPM method is proposed to provide a tight connection between PMs, ERs, FPs, and MVDs and to improve the reusability of predefined ERs and FPs. The theoretical framework is based on the approach of the Georgia Tech Process to Product Modeling (GTPPM) to suit the IDM development process. An xPPM tool is developed, and the validity of xPPM is analyzed through the reproduction of existing IDMs and MVDs. The benefits and limitations of xPPM and lessons from the applicability tests are discussed.

Original languageEnglish
Pages (from-to)636-651
Number of pages16
JournalAdvanced Engineering Informatics
Issue number4
Publication statusPublished - 2013 Oct

Bibliographical note

Funding Information:
This research was supported by the Technology Innovation Program (World Best Software Project, 10040794) of the Ministry of Science, ICT & Future Planning (MSIP, Korea), and also partially by the Science, ICT & Future Planning, Korea, under the C-ITRC (Convergence Information Technology Research Center) support program (NIPA-2013-H0401-13-1003) supervised by the NIPA (National IT Industry Promotion Agency).

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Artificial Intelligence


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